Comparison of Corrupted Sensor Data Detection Methods in Detecting Stealthy Attacks on Cyber-Physical Systems

2017 ◽  
Author(s):  
Giedre Sabaliauskaite ◽  
Geok See Ng ◽  
Justin Ruths ◽  
Aditya Mathur
Keyword(s):  
Cyber Physical Systems ◽  
Sensor Data ◽  
Detection Methods ◽  
Data Detection ◽  
Physical Systems ◽  
Stealthy Attacks

Brief Survey on Attack Detection Methods for Cyber-Physical Systems

2020 ◽  
Vol 14 (4) ◽  
pp. 5329-5339 ◽  
Author(s):  
Sen Tan ◽  
Josep M. Guerrero ◽  
Peilin Xie ◽  
Renke Han ◽  
Juan C. Vasquez
Keyword(s):  
Cyber Physical Systems ◽  
Attack Detection ◽  
Detection Methods ◽  
Physical Systems

scholarly journals Privacy-Preserving Broker-ABE Scheme for Multiple Cloud-Assisted Cyber Physical Systems

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5463 ◽  
Author(s):  
Po-Wen Chi ◽  
Ming-Hung Wang
Keyword(s):  
Data Privacy ◽  
Service Providers ◽  
Real Life ◽  
Data Communication ◽  
Physical Space ◽  
Cloud Service ◽  
Cyber Physical Systems ◽  
Privacy Preserving ◽  
Sensor Data ◽  
Physical Systems

Cloud-assisted cyber–physical systems (CCPSs) integrate the physical space with cloud computing. To do so, sensors on the field collect real-life data and forward it to clouds for further data analysis and decision-making. Since multiple services may be accessed at the same time, sensor data should be forwarded to different cloud service providers (CSPs). In this scenario, attribute-based encryption (ABE) is an appropriate technique for securing data communication between sensors and clouds. Each cloud has its own attributes and a broker can determine which cloud is authorized to access data by the requirements set at the time of encryption. In this paper, we propose a privacy-preserving broker-ABE scheme for multiple CCPSs (MCCPS). The ABE separates the policy embedding job from the ABE task. To ease the computational burden of the sensors, this scheme leaves the policy embedding task to the broker, which is generally more powerful than the sensors. Moreover, the proposed scheme provides a way for CSPs to protect data privacy from outside coercion.

scholarly journals A GENERIC TRUST MANAGEMENT FRAMEWORK FOR HETEROGENEOUS SENSORS IN CYBER PHYSICAL SYSTEMS

2017 ◽  
Vol 10 (13) ◽  
pp. 176 ◽  
Author(s):  
Kanchana Devi V ◽  
Ganesan R
Keyword(s):  
Trust Management ◽  
Human Life ◽  
Cyber Physical Systems ◽  
Sensor Data ◽  
Network Simulator ◽  
Sensor Reading ◽  
Detection Range ◽  
Management Framework ◽  
Heterogeneous Sensors ◽  
Physical Systems

Objective: “Wireless Technology” is the magic word in today’s era. In which, Cyber Physical Systems (CPS) is the booming world which binds the physical world and cyber world together. The CPS is also called as Safety Critical System because of the human life involvement. In this emerging technology, lots of heterogeneous sensors are involved and each sensor will play an important role. If something goes wrong with sensor or sensor data. It will definitely affect the human life involved in it.Methods: In this paper, we proposed a generic trust management framework for heterogeneous sensors which will detect the sensor data falsification (Data Integrity), faulty sensor reading, and packet dropping nodes (Selfish Nodes) through rules and rating concept.Results: The efficiency of the proposed framework is evaluated with the help of Network Simulator 2 (NS-2.35). The maximum numbers of untrusted nodes are identified in point 0.40 than Multi-Level Trust Framework for Wireless Sensor Network (MTF-WSN) and Framework for Packet-Droppers Mitigation (FPDM). It is also evident that Trust Management Framework for Cyber Physical Systems (TRMF-CPS) identifies maximum number of untrusted nodes in the detection range of 0.35 and 0.45. Therefore, 0.35 and 0.45 are considered as maximum and minimum threshold points for effective untrusted nodes. Conclusion:The experimentation results and comparative study shows that, our trust management framework will easily detected sensors which misbehave. 

scholarly journals Adversarial Regression for Detecting Attacks in Cyber-Physical Systems

2018 ◽  
Author(s):  
Amin Ghafouri ◽  
Yevgeniy Vorobeychik ◽  
Xenofon Koutsoukos
Keyword(s):  
Stackelberg Game ◽  
Cyber Physical Systems ◽  
Learning Approaches ◽  
Physical Damage ◽  
Detection Thresholds ◽  
Physical Systems ◽  
System Resilience ◽  
Common Learning ◽  
Stealthy Attacks ◽  
Stealthy Attack

Attacks in cyber-physical systems (CPS) which manipulate sensor readings can cause enormous physical damage if undetected. Detection of attacks on sensors is crucial to mitigate this issue. We study supervised regression as a means to detect anomalous sensor readings, where each sensor's measurement is predicted as a function of other sensors. We show that several common learning approaches in this context are still vulnerable to stealthy attacks, which carefully modify readings of compromised sensors to cause desired damage while remaining undetected. Next, we model the interaction between the CPS defender and attacker as a Stackelberg game in which the defender chooses detection thresholds, while the attacker deploys a stealthy attack in response. We present a heuristic algorithm for finding an approximately optimal threshold for the defender in this game, and show that it increases system resilience to attacks without significantly increasing the false alarm rate.

scholarly journals A Multiplicative Coordinated Stealthy Attack for Nonlinear Cyber-Physical Systems with Homogeneous Property

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Gyujin Na ◽  
Hanbit Lee ◽  
Yongsoon Eun
Keyword(s):  
Dynamic Systems ◽  
Cyber Physical Systems ◽  
Attack Detection ◽  
Property A ◽  
Physical Systems ◽  
Stealthy Attacks ◽  
Detection Mechanisms ◽  
Nonlinear Nature ◽  
System Knowledge ◽  
Stealthy Attack

Stealthy attacks to cyber-physical systems (CPS) refer to the ones that avoid attack detection mechanisms augmented to the systems typically in the form of anomaly detectors. Various types of stealthy attacks have been reported in the literature. Among the attacks with stealthy property, a recently reported multiplicative coordinated attack is particularly dangerous in that it corrupts sensor and actuator data in a coordinated manner, and it does not require precise system knowledge in order to be stealthy. It must be noted that most of these attacks are applicable to CPS, the physical counterparts of which are of linear dynamics. This could be a limitation since most of the physical dynamic systems that are encountered from CPS perspective are of nonlinear nature. In this work, we present a version of multiplicative coordinated stealthy attack for a class of CPS, the physical counterpart of which possesses nonlinear dynamics. Specifically, for the physical systems with homogeneous property, the attack is constructed and the effect is analyzed. Various simulations are carried out to illustrate the effect of the attack.

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